2022 Vol. 39, No. 11
Display Method:
2022, 39(11): 1-1.
Abstract:
2022, 39(11): 1789-1799.
doi: 10.1007/s00376-022-2212-1
Abstract:
To improve understanding of essential aspects that influence forecasting of tropical cyclones (TCs), the National Key Research and Development Program, Ministry of Science and Technology of the People’s Republic of China conducted a five-year project titled “Key Dynamic and Thermodynamic Processes and Prediction for the Evolution of Typhoon Intensity and Structure” (KPPT). Through this project, new understandings of TC intensification, including outer rainband-driven secondary eyewall formation and the roles of boundary layer dynamics and vertical wind shear, and improvements to TC data assimilation with integrated algorithms and adaptive localizations are achieved. To promote a breakthrough in TC intensity and structure forecasting, a new paradigm for TC evolution dynamics (i.e., the correlations, interactions, and error propagation among the triangle of TC track, intensity, and structure) is proposed; and an era of dynamic-constrained, big-data driven, and strongly coupled data assimilation at the subkilometer scale and seamless prediction is expected.
To improve understanding of essential aspects that influence forecasting of tropical cyclones (TCs), the National Key Research and Development Program, Ministry of Science and Technology of the People’s Republic of China conducted a five-year project titled “Key Dynamic and Thermodynamic Processes and Prediction for the Evolution of Typhoon Intensity and Structure” (KPPT). Through this project, new understandings of TC intensification, including outer rainband-driven secondary eyewall formation and the roles of boundary layer dynamics and vertical wind shear, and improvements to TC data assimilation with integrated algorithms and adaptive localizations are achieved. To promote a breakthrough in TC intensity and structure forecasting, a new paradigm for TC evolution dynamics (i.e., the correlations, interactions, and error propagation among the triangle of TC track, intensity, and structure) is proposed; and an era of dynamic-constrained, big-data driven, and strongly coupled data assimilation at the subkilometer scale and seamless prediction is expected.
2022, 39(11): 1800-1815.
doi: 10.1007/s00376-021-1209-5
Abstract:
Diabatic heating by convection in the eyewall often produces an annular region of high potential vorticity (PV) around the relatively low PV eye in a strong tropical cyclone (TC). Such a PV ring is barotropically unstable and can encourage the exponential growth of PV waves. In this study, such instability and the subsequent nonlinear evolution of three TC-like vortices having PV rings with different degrees of hollowness on an f-plane are first examined using an unforced, inviscid shallow-water-equation model. Results show that the simulated eyewalls evolve similarly to those in the nondivergent barotropic model. It is also found that the polygonal eyewall structure can be decomposed into vortex Rossby waves (VRWs) of different wavenumbers with different amplitudes, allowing for wave-wave interactions to produce complicated behaviors of mesovortices in the TC eyewall. The same set of PV rings has been examined on a beta-plane. Although the beta effect has been rendered unimportant to the eyewall evolution due to the relatively small scale of the inner-core circulation, this study shows that the beta effect may erode the coherent structure of mesovortices in the eyewall of an initially hollow PV-ring vortex. Mesovortices modeled on the beta-plane with a greater beta parameter tend to experience an earlier breakdown and enhanced radial gradients of the basic-state (azimuthally mean) angular velocity, followed by wave-wave, wave-flow interactions, leading to earlier merger and axisymmetrization processes. This result implies that the beta effect could be one of the forcings that shorten the lifetime of quasi-steady mesovortices in the eyewall of real TCs.
Diabatic heating by convection in the eyewall often produces an annular region of high potential vorticity (PV) around the relatively low PV eye in a strong tropical cyclone (TC). Such a PV ring is barotropically unstable and can encourage the exponential growth of PV waves. In this study, such instability and the subsequent nonlinear evolution of three TC-like vortices having PV rings with different degrees of hollowness on an f-plane are first examined using an unforced, inviscid shallow-water-equation model. Results show that the simulated eyewalls evolve similarly to those in the nondivergent barotropic model. It is also found that the polygonal eyewall structure can be decomposed into vortex Rossby waves (VRWs) of different wavenumbers with different amplitudes, allowing for wave-wave interactions to produce complicated behaviors of mesovortices in the TC eyewall. The same set of PV rings has been examined on a beta-plane. Although the beta effect has been rendered unimportant to the eyewall evolution due to the relatively small scale of the inner-core circulation, this study shows that the beta effect may erode the coherent structure of mesovortices in the eyewall of an initially hollow PV-ring vortex. Mesovortices modeled on the beta-plane with a greater beta parameter tend to experience an earlier breakdown and enhanced radial gradients of the basic-state (azimuthally mean) angular velocity, followed by wave-wave, wave-flow interactions, leading to earlier merger and axisymmetrization processes. This result implies that the beta effect could be one of the forcings that shorten the lifetime of quasi-steady mesovortices in the eyewall of real TCs.
2022, 39(11): 1816-1832.
doi: 10.1007/s00376-022-1444-4
Abstract:
An ensemble Kalman filter (EnKF) combined with the Advanced Research Weather Research and Forecasting model (WRF) is cycled and evaluated for western North Pacific (WNP) typhoons of year 2016. Conventional in situ data, radiance observations, and tropical cyclone (TC) minimum sea level pressure (SLP) are assimilated every 6 h using an 80-member ensemble. For all TC categories, the 6-h ensemble priors from the WRF/EnKF system have an appropriate amount of variance for TC tracks but have insufficient variance for TC intensity. The 6-h ensemble priors from the WRF/EnKF system tend to overestimate the intensity for weak storms but underestimate the intensity for strong storms. The 5-d deterministic forecasts launched from the ensemble mean analyses of WRF/EnKF are compared to the NCEP and ECMWF operational control forecasts. Results show that the WRF/EnKF forecasts generally have larger track errors than the NCEP and ECMWF forecasts for all TC categories because the regional simulation cannot represent the large-scale environment better than the global simulation. The WRF/EnKF forecasts produce smaller intensity errors and biases than the NCEP and ECMWF forecasts for typhoons, but the opposite is true for tropical storms and severe tropical storms. The 5-d ensemble forecasts from the WRF/EnKF system for seven typhoon cases show appropriate variance for TC track and intensity with short forecast lead times but have insufficient spread with long forecast lead times. The WRF/EnKF system provides better ensemble forecasts and higher predictability for TC intensity than the NCEP and ECMWF ensemble forecasts.
An ensemble Kalman filter (EnKF) combined with the Advanced Research Weather Research and Forecasting model (WRF) is cycled and evaluated for western North Pacific (WNP) typhoons of year 2016. Conventional in situ data, radiance observations, and tropical cyclone (TC) minimum sea level pressure (SLP) are assimilated every 6 h using an 80-member ensemble. For all TC categories, the 6-h ensemble priors from the WRF/EnKF system have an appropriate amount of variance for TC tracks but have insufficient variance for TC intensity. The 6-h ensemble priors from the WRF/EnKF system tend to overestimate the intensity for weak storms but underestimate the intensity for strong storms. The 5-d deterministic forecasts launched from the ensemble mean analyses of WRF/EnKF are compared to the NCEP and ECMWF operational control forecasts. Results show that the WRF/EnKF forecasts generally have larger track errors than the NCEP and ECMWF forecasts for all TC categories because the regional simulation cannot represent the large-scale environment better than the global simulation. The WRF/EnKF forecasts produce smaller intensity errors and biases than the NCEP and ECMWF forecasts for typhoons, but the opposite is true for tropical storms and severe tropical storms. The 5-d ensemble forecasts from the WRF/EnKF system for seven typhoon cases show appropriate variance for TC track and intensity with short forecast lead times but have insufficient spread with long forecast lead times. The WRF/EnKF system provides better ensemble forecasts and higher predictability for TC intensity than the NCEP and ECMWF ensemble forecasts.
2022, 39(11): 1833-1858.
doi: 10.1007/s00376-021-1222-8
Abstract:
To improve the ensemble prediction system of the tropical regional atmosphere model for the South China Sea (TREPS) in predicting landfalling tropical cyclones (TCs), the impacts of three new implementing strategies for surface and model physics perturbations in TREPS were evaluated for 19 TCs making landfall in China during 2014–16. For sea surface temperature (SST) perturbations, spatially uncorrelated random perturbations were replaced with spatially correlated ones. The multiplier f, which is used to form perturbed tendency in the Stochastically Perturbed Parameterization Tendency (SPPT) scheme, was inflated in regions with evident convective activity (f-inflated SPPT). Lastly, the Stochastically Perturbed Parameterization (SPP) scheme with 14 perturbed parameters selected from the planetary boundary layer, surface layer, microphysics, and cumulus convection parameterizations was added. Overall, all these methods improved forecasts more significantly for non-intensifying than intensifying TCs. Compared with f-inflated SPPT, the spatially correlated SST perturbations generally showed comparable performance but were more (less) skillful for intensifying (non-intensifying) TCs. The advantages of the spatially correlated SST perturbations and f-inflated SPPT were mainly present in the deterministic guidance for both TC track and wind and in the probabilistic guidance for reliability of wind. For intensifying TCs, adding SPP led to mixed impacts with significant improvements in probability-matched mean of modest winds and in probabilistic forecasts of rainfall; while for non-intensifying TCs, adding SPP frequently led to positive impacts on the deterministic guidance for track, intensity, strong winds, and moderate rainfall and on the probabilistic guidance for wind and discrimination of rainfall.
To improve the ensemble prediction system of the tropical regional atmosphere model for the South China Sea (TREPS) in predicting landfalling tropical cyclones (TCs), the impacts of three new implementing strategies for surface and model physics perturbations in TREPS were evaluated for 19 TCs making landfall in China during 2014–16. For sea surface temperature (SST) perturbations, spatially uncorrelated random perturbations were replaced with spatially correlated ones. The multiplier f, which is used to form perturbed tendency in the Stochastically Perturbed Parameterization Tendency (SPPT) scheme, was inflated in regions with evident convective activity (f-inflated SPPT). Lastly, the Stochastically Perturbed Parameterization (SPP) scheme with 14 perturbed parameters selected from the planetary boundary layer, surface layer, microphysics, and cumulus convection parameterizations was added. Overall, all these methods improved forecasts more significantly for non-intensifying than intensifying TCs. Compared with f-inflated SPPT, the spatially correlated SST perturbations generally showed comparable performance but were more (less) skillful for intensifying (non-intensifying) TCs. The advantages of the spatially correlated SST perturbations and f-inflated SPPT were mainly present in the deterministic guidance for both TC track and wind and in the probabilistic guidance for reliability of wind. For intensifying TCs, adding SPP led to mixed impacts with significant improvements in probability-matched mean of modest winds and in probabilistic forecasts of rainfall; while for non-intensifying TCs, adding SPP frequently led to positive impacts on the deterministic guidance for track, intensity, strong winds, and moderate rainfall and on the probabilistic guidance for wind and discrimination of rainfall.
2022, 39(11): 1859-1872.
doi: 10.1007/s00376-022-2015-4
Abstract:
Intensity forecasting is one of the most challenging aspects of tropical cyclone (TC) forecasting. This work examines the impact of assimilating high-resolution all-sky infrared radiance observations from geostationary satellite GOES-13 on the convection-permitting initialization and prediction of Hurricane Joaquin (2015) with an ensemble Kalman filter (EnKF) based on the Weather Research and Forecasting (WRF) model. Given that almost all operational global and regional models struggled to capture Hurricane Joaquin (2015)’s intensity, this study examines the potential in improving Joaquin’s prediction when assimilating all-sky infrared radiances from GOES-13’s water vapor channel. It is demonstrated that, after a few 3-hour cycles assimilating all-sky radiance, the WRF model was able to forecast reasonably well Joaquin’s intensity, including its rapid intensification (RI). The improvement was largely due to a more realistic initial hurricane structure with a stronger, warmer, and more compact inner-core. Ensemble forecasts were used to further explore the important physical mechanisms driving the hurricane’s RI. Results showed that the RI forecasts were greatly impacted by the initial inner-core vortex structure.
Intensity forecasting is one of the most challenging aspects of tropical cyclone (TC) forecasting. This work examines the impact of assimilating high-resolution all-sky infrared radiance observations from geostationary satellite GOES-13 on the convection-permitting initialization and prediction of Hurricane Joaquin (2015) with an ensemble Kalman filter (EnKF) based on the Weather Research and Forecasting (WRF) model. Given that almost all operational global and regional models struggled to capture Hurricane Joaquin (2015)’s intensity, this study examines the potential in improving Joaquin’s prediction when assimilating all-sky infrared radiances from GOES-13’s water vapor channel. It is demonstrated that, after a few 3-hour cycles assimilating all-sky radiance, the WRF model was able to forecast reasonably well Joaquin’s intensity, including its rapid intensification (RI). The improvement was largely due to a more realistic initial hurricane structure with a stronger, warmer, and more compact inner-core. Ensemble forecasts were used to further explore the important physical mechanisms driving the hurricane’s RI. Results showed that the RI forecasts were greatly impacted by the initial inner-core vortex structure.
2022, 39(11): 1885-1896.
doi: 10.1007/s00376-022-1347-4
Abstract:
This study investigates the influences of boreal summer intraseasonal oscillation (BSISO), which originates from the equatorial Indian Ocean and prevails over the Indo-Pacific region, on precipitation over Southeast China, including South China and Yangtze River Valley. The results indicate that the BSISO-related precipitation anomalies are remarkably different between early summer (May–June) and late summer (July–August). The BSISO-related precipitation anomalies tend to appear more northward in late summer in comparison with early summer. Accordingly, the BSISO is significantly related to precipitation anomalies over South China during many phases in early summer but related to very weak anomalies during all the phases in late summer. Such northward shifts of precipitation anomalies from early summer to late summer are clearest during phases 4 and 7, when the lower-tropospheric anticyclonic and cyclonic circulation anomalies dominate over the subtropical western North Pacific, respectively. Finally, we explain the differences between early and late summers through the seasonal northward migration of climatological equivalent potential temperature gradient, which is located in the South China during early summer but migrates northward to the YRV during late summer.
This study investigates the influences of boreal summer intraseasonal oscillation (BSISO), which originates from the equatorial Indian Ocean and prevails over the Indo-Pacific region, on precipitation over Southeast China, including South China and Yangtze River Valley. The results indicate that the BSISO-related precipitation anomalies are remarkably different between early summer (May–June) and late summer (July–August). The BSISO-related precipitation anomalies tend to appear more northward in late summer in comparison with early summer. Accordingly, the BSISO is significantly related to precipitation anomalies over South China during many phases in early summer but related to very weak anomalies during all the phases in late summer. Such northward shifts of precipitation anomalies from early summer to late summer are clearest during phases 4 and 7, when the lower-tropospheric anticyclonic and cyclonic circulation anomalies dominate over the subtropical western North Pacific, respectively. Finally, we explain the differences between early and late summers through the seasonal northward migration of climatological equivalent potential temperature gradient, which is located in the South China during early summer but migrates northward to the YRV during late summer.
2022, 39(11): 1897-1913.
doi: 10.1007/s00376-022-1421-y
Abstract:
This study uses linear regression and composite analyses to identify a pronounced asymmetric connection of sea surface temperature (SST) in the Tasman Sea with the two opposite phases of El Niño-Southern Oscillation (ENSO) during austral summer. In El Niño years, the SST anomalies (SSTAs) in the Tasman Sea exhibit a dipolar pattern with weak warmth in the northwest and modest cooling in the southeast, while during La Niña years the SSTAs exhibit a basin-scale warmth with greater amplitude. Investigations into the underlying mechanism suggest that this asymmetry arises from a mechanism related to oceanic heat transport, specifically the anomalous Ekman meridional heat transport induced by the zonal wind stress anomalies, rather than the surface heat fluxes on the air-sea interface. Further analysis reveals that the asymmetry of oceanic heat transport between El Niño and La Niña years is driven by the asymmetric atmospheric circulation over the Tasman Sea stimulated by the asymmetric diabatic heating in the tropical Pacific between the two opposite ENSO phases.
This study uses linear regression and composite analyses to identify a pronounced asymmetric connection of sea surface temperature (SST) in the Tasman Sea with the two opposite phases of El Niño-Southern Oscillation (ENSO) during austral summer. In El Niño years, the SST anomalies (SSTAs) in the Tasman Sea exhibit a dipolar pattern with weak warmth in the northwest and modest cooling in the southeast, while during La Niña years the SSTAs exhibit a basin-scale warmth with greater amplitude. Investigations into the underlying mechanism suggest that this asymmetry arises from a mechanism related to oceanic heat transport, specifically the anomalous Ekman meridional heat transport induced by the zonal wind stress anomalies, rather than the surface heat fluxes on the air-sea interface. Further analysis reveals that the asymmetry of oceanic heat transport between El Niño and La Niña years is driven by the asymmetric atmospheric circulation over the Tasman Sea stimulated by the asymmetric diabatic heating in the tropical Pacific between the two opposite ENSO phases.
2022, 39(11): 1914-1924.
doi: 10.1007/s00376-022-1388-8
Abstract:
This study reveals a significant positive connection between autumn non-tropical-cyclone heavy rainfall on Hainan Island and the intensity of Eastern Pacific (EP) El Niño events. That is, the amount of rainfall in super EP El Niño years is more than that in normal EP El Niño years. Comparing EP El Niño years of different intensities, the cooler sea surface temperature in the northwestern Pacific during super EP El Niño years stimulates a negative surface latent heat flux (LHF) anomaly and abnormal anticyclonic circulation at 850 hPa. Under these conditions, an abnormal zonal vertical circulation develops in the northern South China Sea once a positive LHF anomaly and abnormal cyclonic circulation (ACC) at 850 hPa occur in the Beibu Gulf. The abnormal zonal vertical circulation further strengthens the ascending motion over Hainan Island, as the critical factor that leads to excessive rainfall. Further analysis shows that the positive LHF anomaly, which can be attributed to the increased latent heat transfer which resulted from the increased surface wind speed, is an important trigger for the ACC. However, the ACC is also the supplier of favorable moisture conditions because it intensifies vapor convergence over Hainan Island and meridionally transports moisture from the South China Sea to northeastern Hainan Island, thereby generating heavy rainfall. This paper emphasizes that the impact of El Niño events, especially super El Niño events, on rainfall over Hainan Island cannot be ignored, even if the traditional view is that frequent rainfall occurs mainly in La Niña years.
This study reveals a significant positive connection between autumn non-tropical-cyclone heavy rainfall on Hainan Island and the intensity of Eastern Pacific (EP) El Niño events. That is, the amount of rainfall in super EP El Niño years is more than that in normal EP El Niño years. Comparing EP El Niño years of different intensities, the cooler sea surface temperature in the northwestern Pacific during super EP El Niño years stimulates a negative surface latent heat flux (LHF) anomaly and abnormal anticyclonic circulation at 850 hPa. Under these conditions, an abnormal zonal vertical circulation develops in the northern South China Sea once a positive LHF anomaly and abnormal cyclonic circulation (ACC) at 850 hPa occur in the Beibu Gulf. The abnormal zonal vertical circulation further strengthens the ascending motion over Hainan Island, as the critical factor that leads to excessive rainfall. Further analysis shows that the positive LHF anomaly, which can be attributed to the increased latent heat transfer which resulted from the increased surface wind speed, is an important trigger for the ACC. However, the ACC is also the supplier of favorable moisture conditions because it intensifies vapor convergence over Hainan Island and meridionally transports moisture from the South China Sea to northeastern Hainan Island, thereby generating heavy rainfall. This paper emphasizes that the impact of El Niño events, especially super El Niño events, on rainfall over Hainan Island cannot be ignored, even if the traditional view is that frequent rainfall occurs mainly in La Niña years.
2022, 39(11): 1925-1940.
doi: 10.1007/s00376-022-1348-3
Abstract:
Extreme Mei-yu rainfall (MYR) can cause catastrophic impacts to the economic development and societal welfare in China. While significant improvements have been made in climate models, they often struggle to simulate local-to-regional extreme rainfall (e.g., MYR). Yet, large-scale climate modes (LSCMs) are relatively well represented in climate models. Since there exists a close relationship between MYR and various LSCMs, it might be possible to develop causality-guided statistical models for MYR prediction based on LSCMs. These statistical models could then be applied to climate model simulations to improve the representation of MYR in climate models. In this pilot study, it is demonstrated that skillful causality-guided statistical models for MYR can be constructed based on known LSCMs. The relevancy of the selected predictors for statistical models are found to be consistent with the literature. The importance of temporal resolution in constructing statistical models for MYR is also shown and is in good agreement with the literature. The results demonstrate the reliability of the causality-guided approach in studying complex circulation systems such as the East Asian summer monsoon (EASM). Some limitations and possible improvements of the current approach are discussed. The application of the causality-guided approach opens up a new possibility to uncover the complex interactions in the EASM in future studies.
Extreme Mei-yu rainfall (MYR) can cause catastrophic impacts to the economic development and societal welfare in China. While significant improvements have been made in climate models, they often struggle to simulate local-to-regional extreme rainfall (e.g., MYR). Yet, large-scale climate modes (LSCMs) are relatively well represented in climate models. Since there exists a close relationship between MYR and various LSCMs, it might be possible to develop causality-guided statistical models for MYR prediction based on LSCMs. These statistical models could then be applied to climate model simulations to improve the representation of MYR in climate models. In this pilot study, it is demonstrated that skillful causality-guided statistical models for MYR can be constructed based on known LSCMs. The relevancy of the selected predictors for statistical models are found to be consistent with the literature. The importance of temporal resolution in constructing statistical models for MYR is also shown and is in good agreement with the literature. The results demonstrate the reliability of the causality-guided approach in studying complex circulation systems such as the East Asian summer monsoon (EASM). Some limitations and possible improvements of the current approach are discussed. The application of the causality-guided approach opens up a new possibility to uncover the complex interactions in the EASM in future studies.
2022, 39(11): 1941-1955.
doi: 10.1007/s00376-022-1360-7
Abstract:
The change in ocean net surface heat flux plays an important role in the climate system. It is closely related to the ocean heat content change and ocean heat transport, particularly over the North Atlantic, where the ocean loses heat to the atmosphere, affecting the AMOC (Atlantic Meridional Overturning Circulation) variability and hence the global climate. However, the difference between simulated surface heat fluxes is still large due to poorly represented dynamical processes involving multiscale interactions in model simulations. In order to explain the discrepancy of the surface heat flux over the North Atlantic, datasets from nineteen AMIP6 and eight highresSST-present climate model simulations are analyzed and compared with the DEEPC (Diagnosing Earth's Energy Pathways in the Climate system) product. As an indirect check of the ocean surface heat flux, the oceanic heat transport inferred from the combination of the ocean surface heat flux, sea ice, and ocean heat content tendency is compared with the RAPID (Rapid Climate Change-Meridional Overturning Circulation and Heat flux array) observations at 26°N in the Atlantic. The AMIP6 simulations show lower inferred heat transport due to less heat loss to the atmosphere. The heat loss from the AMIP6 ensemble mean north of 26°N in the Atlantic is about 10 W m–2 less than DEEPC, and the heat transport is about 0.30 PW (1 PW = 1015 W) lower than RAPID and DEEPC. The model horizontal resolution effect on the discrepancy is also investigated. Results show that by increasing the resolution, both surface heat flux north of 26°N and heat transport at 26°N in the Atlantic can be improved.
The change in ocean net surface heat flux plays an important role in the climate system. It is closely related to the ocean heat content change and ocean heat transport, particularly over the North Atlantic, where the ocean loses heat to the atmosphere, affecting the AMOC (Atlantic Meridional Overturning Circulation) variability and hence the global climate. However, the difference between simulated surface heat fluxes is still large due to poorly represented dynamical processes involving multiscale interactions in model simulations. In order to explain the discrepancy of the surface heat flux over the North Atlantic, datasets from nineteen AMIP6 and eight highresSST-present climate model simulations are analyzed and compared with the DEEPC (Diagnosing Earth's Energy Pathways in the Climate system) product. As an indirect check of the ocean surface heat flux, the oceanic heat transport inferred from the combination of the ocean surface heat flux, sea ice, and ocean heat content tendency is compared with the RAPID (Rapid Climate Change-Meridional Overturning Circulation and Heat flux array) observations at 26°N in the Atlantic. The AMIP6 simulations show lower inferred heat transport due to less heat loss to the atmosphere. The heat loss from the AMIP6 ensemble mean north of 26°N in the Atlantic is about 10 W m–2 less than DEEPC, and the heat transport is about 0.30 PW (1 PW = 1015 W) lower than RAPID and DEEPC. The model horizontal resolution effect on the discrepancy is also investigated. Results show that by increasing the resolution, both surface heat flux north of 26°N and heat transport at 26°N in the Atlantic can be improved.
2022, 39(11): 1956-1968.
doi: 10.1007/s00376-022-1450-6
Abstract:
This study reexamines the correlation between the size and intensity of tropical cyclones (TCs) over the western North Pacific from the perspective of individual TCs, rather than the previous large-sample framework mixing up all TC records. Statistics show that the positive size-intensity correlation based on individual TCs is relatively high. However, this correlation is obscured by mixing large samples. The weakened correlation based on all TC records is primarily due to the diversity in the size change relative to the same intensity change among TCs, which can be quantitatively measured by the linear regression coefficient (RC) of size against intensity. To further explore the factors that cause the variability in RCs that weakens the size-intensity correlation when considering all TC records, the TCs from 2001 to 2020 are classified into two groups according to their RC magnitudes, within which the high-RC TCs have a larger size expansion than the low-RC TCs given the same intensity change. Two key mechanisms responsible for the RC differences are proposed. First, the high-RC TCs are generally located at higher latitudes than the low-RC TCs, resulting in higher planetary vorticity and thus higher planetary angular momentum import at low levels. Second, the high-RC TCs are susceptible to stronger environmental vertical wind shear, leading to more prolific outer convection than the low-RC TCs. The positive feedback between outer diabatic heating and boundary layer inflow favors the inward import of absolute angular momentum in the outer region, thereby contributing to a larger size expansion in the high-RC TCs.
This study reexamines the correlation between the size and intensity of tropical cyclones (TCs) over the western North Pacific from the perspective of individual TCs, rather than the previous large-sample framework mixing up all TC records. Statistics show that the positive size-intensity correlation based on individual TCs is relatively high. However, this correlation is obscured by mixing large samples. The weakened correlation based on all TC records is primarily due to the diversity in the size change relative to the same intensity change among TCs, which can be quantitatively measured by the linear regression coefficient (RC) of size against intensity. To further explore the factors that cause the variability in RCs that weakens the size-intensity correlation when considering all TC records, the TCs from 2001 to 2020 are classified into two groups according to their RC magnitudes, within which the high-RC TCs have a larger size expansion than the low-RC TCs given the same intensity change. Two key mechanisms responsible for the RC differences are proposed. First, the high-RC TCs are generally located at higher latitudes than the low-RC TCs, resulting in higher planetary vorticity and thus higher planetary angular momentum import at low levels. Second, the high-RC TCs are susceptible to stronger environmental vertical wind shear, leading to more prolific outer convection than the low-RC TCs. The positive feedback between outer diabatic heating and boundary layer inflow favors the inward import of absolute angular momentum in the outer region, thereby contributing to a larger size expansion in the high-RC TCs.
2022, 39(11): 1969-1981.
doi: 10.1007/s00376-022-1403-0
Abstract:
This study depicts the sub-seasonal prediction of the South China Sea summer monsoon onset (SCSSMO) and investigates the associated oceanic and atmospheric processes, utilizing the hindcasts of the National Centers for Environmental Prediction (NCEP) Climate Forecast System version 2 (CFSv2). Typically, the SCSSMO is accompanied by an eastward retreat of the western North Pacific subtropical high (WNPSH), development of the cross-equatorial flow, and an increase in the east-west sea surface temperature (SST) gradient. These features are favorable for the onset of westerlies and strengthening of convection and precipitation over the South China Sea (SCS). A more vigorous SCSSMO process shows a higher predictability, and vice versa. The NCEP CFSv2 can successfully predict the onset date and evolution of the monsoon about 4 pentads (20 days) in advance (within 1–2 pentads) for more forceful (less vigorous) SCSSMO processes. On the other hand, the climatological SCSSMO that occurs around the 27th pentad can be accurately predicted in one pentad, and the predicted SCSSMO occurs 1–2 pentads earlier than the observed with a weaker intensity at longer leadtimes. Warm SST biases appear over the western equatorial Pacific preceding the SCSSMO. These biases induce a weaker-than-observed WNPSH as a Gill-type response, leading to weakened low-level easterlies over the SCS and hence an earlier and less vigorous SCSSMO. In addition, after the SCSSMO, remarkable warm biases over the eastern Indian Ocean and the SCS and cold biases over the WNP induce weaker-than-observed westerlies over the SCS, thus also contributing to the less vigorous SCSSMO.
This study depicts the sub-seasonal prediction of the South China Sea summer monsoon onset (SCSSMO) and investigates the associated oceanic and atmospheric processes, utilizing the hindcasts of the National Centers for Environmental Prediction (NCEP) Climate Forecast System version 2 (CFSv2). Typically, the SCSSMO is accompanied by an eastward retreat of the western North Pacific subtropical high (WNPSH), development of the cross-equatorial flow, and an increase in the east-west sea surface temperature (SST) gradient. These features are favorable for the onset of westerlies and strengthening of convection and precipitation over the South China Sea (SCS). A more vigorous SCSSMO process shows a higher predictability, and vice versa. The NCEP CFSv2 can successfully predict the onset date and evolution of the monsoon about 4 pentads (20 days) in advance (within 1–2 pentads) for more forceful (less vigorous) SCSSMO processes. On the other hand, the climatological SCSSMO that occurs around the 27th pentad can be accurately predicted in one pentad, and the predicted SCSSMO occurs 1–2 pentads earlier than the observed with a weaker intensity at longer leadtimes. Warm SST biases appear over the western equatorial Pacific preceding the SCSSMO. These biases induce a weaker-than-observed WNPSH as a Gill-type response, leading to weakened low-level easterlies over the SCS and hence an earlier and less vigorous SCSSMO. In addition, after the SCSSMO, remarkable warm biases over the eastern Indian Ocean and the SCS and cold biases over the WNP induce weaker-than-observed westerlies over the SCS, thus also contributing to the less vigorous SCSSMO.
2022, 39(11): 1873-1884.
doi: 10.1007/s00376-022-2030-5
Abstract:
Following the High-Resolution Model Intercomparison Project (HighResMIP) Tier 2 protocol under the Coupled Model Intercomparison Project Phase 6 (CMIP6), three numerical experiments are conducted with the Chinese Academy of Sciences Flexible Global Ocean-Atmosphere-Land System Model, version f3-H (CAS FGOALS-f3-H), and a 101-year (1950–2050) global high-resolution simulation dataset is presented in this study. The basic configuration of the FGOALS-f3-H model and numerical experiments design are briefly described, and then the historical simulation is validated. Forced by observed radiative agents from 1950 to 2014, the coupled model essentially reproduces the observed long-term trends of temperature, precipitation, and sea ice extent, as well as the large-scale pattern of temperature and precipitation. With an approximate 0.25º horizontal resolution in the atmosphere and 0.1° in the ocean, the coupled models also simulate energetic western boundary currents and the Antarctic Circulation Current (ACC), reasonable characteristics of extreme precipitation, and realistic frontal scale air-sea interaction. The dataset and supporting detailed information have been published in the Earth System Grid Federation (ESGF,https://esgf-node.llnl.gov/projects/cmip6/ ).
Following the High-Resolution Model Intercomparison Project (HighResMIP) Tier 2 protocol under the Coupled Model Intercomparison Project Phase 6 (CMIP6), three numerical experiments are conducted with the Chinese Academy of Sciences Flexible Global Ocean-Atmosphere-Land System Model, version f3-H (CAS FGOALS-f3-H), and a 101-year (1950–2050) global high-resolution simulation dataset is presented in this study. The basic configuration of the FGOALS-f3-H model and numerical experiments design are briefly described, and then the historical simulation is validated. Forced by observed radiative agents from 1950 to 2014, the coupled model essentially reproduces the observed long-term trends of temperature, precipitation, and sea ice extent, as well as the large-scale pattern of temperature and precipitation. With an approximate 0.25º horizontal resolution in the atmosphere and 0.1° in the ocean, the coupled models also simulate energetic western boundary currents and the Antarctic Circulation Current (ACC), reasonable characteristics of extreme precipitation, and realistic frontal scale air-sea interaction. The dataset and supporting detailed information have been published in the Earth System Grid Federation (ESGF,
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